{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0",
   "metadata": {},
   "source": [
    "[![image](https://jupyterlite.rtfd.io/en/latest/_static/badge.svg)](https://demo.leafmap.org/lab/index.html?path=notebooks/84_read_parquet.ipynb)\n",
    "[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/opengeos/leafmap/blob/master/docs/notebooks/84_read_parquet.ipynb)\n",
    "[![image](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/opengeos/leafmap/HEAD)\n",
    "\n",
    "**Reading GeoParquet files and visualizing vector data interactively**\n",
    "\n",
    "Uncomment the following line to install [leafmap](https://leafmap.org) if needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# %pip install -U leafmap lonboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import leafmap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3",
   "metadata": {},
   "source": [
    "Visualizing point data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"https://github.com/opengeos/data/raw/refs/heads/main/duckdb/cities.parquet\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5",
   "metadata": {},
   "source": [
    "Read GeoParquet and return a GeoPandas GeoDataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6",
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf = leafmap.read_parquet(url, return_type=\"gdf\", src_crs=\"EPSG:4326\")\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7",
   "metadata": {},
   "source": [
    "View the GeoDataFrame interactively using folium."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8",
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf.explore()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9",
   "metadata": {},
   "source": [
    "Visualize the GeoDataFrame using lonboard."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10",
   "metadata": {},
   "outputs": [],
   "source": [
    "leafmap.view_vector(gdf, get_radius=20000, get_fill_color=\"blue\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11",
   "metadata": {},
   "source": [
    "Visualizing polygon data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"https://data.source.coop/giswqs/nwi/wetlands/DC_Wetlands.parquet\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13",
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf = leafmap.read_parquet(\n",
    "    url, return_type=\"gdf\", src_crs=\"EPSG:5070\", dst_crs=\"EPSG:4326\"\n",
    ")\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14",
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf.explore()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15",
   "metadata": {},
   "outputs": [],
   "source": [
    "leafmap.view_vector(gdf, get_fill_color=[0, 0, 255, 128])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16",
   "metadata": {},
   "source": [
    "![vector](https://i.imgur.com/HRtpiVd.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17",
   "metadata": {},
   "source": [
    "Alternatively, you can specify a color map to visualize the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18",
   "metadata": {},
   "outputs": [],
   "source": [
    "color_map = {\n",
    "    \"Freshwater Forested/Shrub Wetland\": (0, 136, 55),\n",
    "    \"Freshwater Emergent Wetland\": (127, 195, 28),\n",
    "    \"Freshwater Pond\": (104, 140, 192),\n",
    "    \"Estuarine and Marine Wetland\": (102, 194, 165),\n",
    "    \"Riverine\": (1, 144, 191),\n",
    "    \"Lake\": (19, 0, 124),\n",
    "    \"Estuarine and Marine Deepwater\": (0, 124, 136),\n",
    "    \"Other\": (178, 134, 86),\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "19",
   "metadata": {},
   "outputs": [],
   "source": [
    "leafmap.view_vector(gdf, color_column=\"WETLAND_TYPE\", color_map=color_map, opacity=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20",
   "metadata": {},
   "source": [
    "![vector-color](https://i.imgur.com/Ejh8hK6.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21",
   "metadata": {},
   "source": [
    "Display a legend for the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "22",
   "metadata": {},
   "outputs": [],
   "source": [
    "leafmap.Legend(title=\"Wetland Type\", legend_dict=color_map)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23",
   "metadata": {},
   "source": [
    "![legend](https://i.imgur.com/fxzHHFN.png)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "geo",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 "nbformat": 4,
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